Peptide-based therapeutics hold great promise for the treatment of various diseases;however,their clinical application is often hindered by toxicity challenges.The accurate prediction of peptide toxicity is crucial fo...Peptide-based therapeutics hold great promise for the treatment of various diseases;however,their clinical application is often hindered by toxicity challenges.The accurate prediction of peptide toxicity is crucial for designing safe peptide-based therapeutics.While traditional experimental approaches are time-consuming and expensive,computational methods have emerged as viable alternatives,including similarity-based and machine learning(ML)-/deep learning(DL)-based methods.However,existing methods often struggle with robustness and generalizability.To address these challenges,we propose HyPepTox-Fuse,a novel framework that fuses protein language model(PLM)-based embeddings with conventional descriptors.HyPepTox-Fuse integrates ensemble PLM-based embeddings to achieve richer peptide representations by leveraging a cross-modal multi-head attention mechanism and Transformer architecture.A robust feature ranking and selection pipeline further refines conventional descriptors,thus enhancing prediction performance.Our framework outperforms state-of-the-art methods in cross-validation and independent evaluations,offering a scalable and reliable tool for peptide toxicity prediction.Moreover,we conducted a case study to validate the robustness and generalizability of HyPepTox-Fuse,highlighting its effectiveness in enhancing model performance.Furthermore,the HyPepTox-Fuse server is freely accessible at https://balalab-skku.org/HyPepTox-Fuse/and the source code is publicly available at https://github.com/cbbl-skku-org/HyPepTox-Fuse/.The study thus presents an intuitive platform for predicting peptide toxicity and supports reproducibility through openly available datasets.展开更多
The explosive growth of lithium-ion battery literature has led to severe knowledge overload,challenging researchers'ability to efficiently extract structured information.While large language models(LLMs)offer cons...The explosive growth of lithium-ion battery literature has led to severe knowledge overload,challenging researchers'ability to efficiently extract structured information.While large language models(LLMs)offer considerable potential for automating this task,their practical application in scientific domains is nonetheless constrained by high application programming interface(API)costs and computational resources required for fine-tuning.To address these limitations,a cognition-enhanced instruction framework(CEIF)is proposed,wherein a high-performance teacher model(such as DeepSeek-R1)provides dynamic feedback,prompt refinement,and training data optimization to guide the learning process of low-parameter models.Experimental results demonstrate that the low-parameter models(6B-9B)optimized via the CEIF achieve approximately 85%accuracy in battery literature extraction tasks,approaching the performance of GPT-4 while requiring only a single NVIDIA RTX 3090 GPU.Furthermore,the emergence of an"Aha moment"characterized by rapid performance improvement during specialized learning is observed,offering novel theoretical insights for the design and optimization of domainspecific models.展开更多
Covalent organic frameworks(COFs)are crystalline materials composed of covalently bonded organic ligands with chemically permeable structures.Their crystallization is achieved by balancing thermal reversibility with t...Covalent organic frameworks(COFs)are crystalline materials composed of covalently bonded organic ligands with chemically permeable structures.Their crystallization is achieved by balancing thermal reversibility with the dynamic nature of the frameworks.Ionic covalent organic frameworks(ICOFs)are a subclass that incorporates ions in positive,negative,or zwitterionic forms into the frameworks.In particular,spiroborate-derived linkages enhance both the structural diversity and functionality of ICOFs.Unlike electroneutral COFs,ICOFs can be tailored by adjusting the types and arrangements of ions,influencing their formation mechanisms and physical properties.This study focuses on analyzing the graph-based structural characteristics of ICOFs with spiroborate linkages.We compute graph based entropy using hybrid topological descriptors that capture both local and global structural patterns.Furthermore,statistical regression models are developed to predict graph energies of larger-dimensional ICOF structures based on these descriptors.To ensure the robustness and accuracy of our results,we validated our findings using a pseudocode algorithm specifically designed for computing degree-based topological indices.This computational validation confirms the consistency of the derived descriptors and supports their applicability in quantitative structure-property relationship(QSPR)modeling.Overall,this approach provides valuable insights for future applications in material design and property prediction within the framework of ICOFs.展开更多
Globally,the integration of traditional medicine and modern medicine has been recognized as a global health priority aimed at improving healthcare accessibility,cultural relevance,and therapeutic effectiveness.This re...Globally,the integration of traditional medicine and modern medicine has been recognized as a global health priority aimed at improving healthcare accessibility,cultural relevance,and therapeutic effectiveness.This review systematically examines the global landscape of traditional medicine-modern medicine integration by analyzing policy developments,regulatory frameworks,and clinical implementation models across various regions,including Asia,Africa,Europe,and the USA.The scope of the review encompasses five key domains:(1)global policy initiatives,(2)regulatory and institutional frameworks,(3)clinical integration models,(4)impacts and outcomes of integrative practices,and(5)challenges and barriers to implementation.Based on peer-reviewed literature and official health policy documents published between 2000 and 2025,the present review investigates how countries have operationalized clinical integration models combining traditional and complementary medicine.Although interest in traditional and complementary medicine has grown worldwide,persistent challenges,such as limited scientific validation,lack of standardization,and professional resistance,continue to hinder progress.This review concludes that successful and sustainable integration requires evidence-based clinical approaches,inclusive regulatory reforms,and coordinated policy strategies.Countries such as China,India,and Brazil have made significant advances,offering valuable models for future implementation worldwide.展开更多
We proposes an AI-assisted framework for integrated natural disaster prevention and emergency response,leveraging the DeepSeek large language model(LLM)to advance intelligent decision-making in geohazard management.We...We proposes an AI-assisted framework for integrated natural disaster prevention and emergency response,leveraging the DeepSeek large language model(LLM)to advance intelligent decision-making in geohazard management.We systematically analyze the technical pathways for deploying LLMs in disaster scenarios,emphasizing three breakthrough directions:(1)knowledge graph-driven dynamic risk modeling,(2)reinforcement learning-optimized emergency decision systems,and(3)secure local deployment architectures.The DeepSeek model demonstrates unique advantages through its hybrid reasoning mechanism combining semantic analysis with geospatial pattern recognition,enabling cost-effective processing of multi-source data spanning historical disaster records,real-time IoT sensor feeds,and socio-environmental parameters.A modular system architecture is designed to achieve three critical objectives:(a)automated construction of domain-specific knowledge graphs through unsupervised learning of disaster physics relationships,(b)scenario-adaptive resource allocation using risk simulations,and(c)preserving emergency coordination via federated learning across distributed response nodes.The proposed local deployment paradigm addresses critical data security concerns in cross-border disaster management while complying with the FAIR principles(Findable,Accessible,Interoperable,Reusable)for geoscientific data governance.This work establishes a methodological foundation for next-generation AI-earth science convergence in disaster mitigation.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
The Upper Triassic Xujiahe （须家河） Formation in the Sichuan （四川） Basin, Southwest China is distinctive for the basin-scale sand deposition. This relatively rare sedimentary phenomenon has not been well interpre...The Upper Triassic Xujiahe （须家河） Formation in the Sichuan （四川） Basin, Southwest China is distinctive for the basin-scale sand deposition. This relatively rare sedimentary phenomenon has not been well interpreted. Here we addressed this issue by discussing sedimentary framework and conceptual model. Analysis of sedimentary setting implied that the basin received transgression during the deposition. It had multiple provenance supplies and river networks, as being surrounded by old- lands in multiple directions including the north, east and south. Thus, the basin was generally charac-terized by coastal and widely open and shallow lacustrine deposition during the Late Triassic Xujiahe period. This is similar to the modern well-known Poyang （鄱阳） Lake. Therefore, we investigated the framework and conceptual model of the Sichuan Basin during the Xujiahe period with an analogue to the Poyang Lake. Results show that the conceptual model of the deposition can be divided into transgressive and regressive stages. The first, third and fifth mem- bers of the formation are in transgressive stage and the deposits are dominated by shore and shallow lacustrine mud. In contrast, the deposition is mainly of braided river channel sand deposits during the regressive stage, mainly including the second, fourth and sixth members of the formation. The sand deposited in almost the entire basin because of the lateral migration and forward moving of the cross networks of the braided rivers. The multiple alternations of short and rapid transgression and relatively long regression are beneficial to the basin-scale sand deposition. Thus, the main channel of the braided river and its extensional areas are favorable for the development of hydrocarbon reservoir. This provides practical significance to the reservoir evaluation and exploration. In addition, the results also justify the relatively distinctive sedimentary phenomenon in the study area and may also have im- plications for understanding the large-scale sand deposition elsewhere.展开更多
The dynamical framework of the nine-level version of the IAP AGCM is presented in this paper. The emphasis of the model's description is put on the following two aspects:(1) A model's standard atmosphere, whic...The dynamical framework of the nine-level version of the IAP AGCM is presented in this paper. The emphasis of the model's description is put on the following two aspects:(1) A model's standard atmosphere, which is a satisfactory approximation to the observed troposphere and lower stratosphere standard atmosphere, is introduced into the equations of the model to permit a more accurate calculation of the vertical transport terms, especially near the tropopause; (2) The vertical levels of the model are carefully selected to guarantee a smooth dependence of layer thickness upon pressure in order to reduce the truncation error involved in the unequal interval vertical finite-differencing. For testing the model, two kinds of linear baroclinic Rossby-Haurwitz waves, one of which has a dynamically stable vertical structure and the other has a relatively unstable one, are constructed to provide initial conditions for numerical experiments. The two waves have been integrated for more than 300 days and 100 days respectively by using the model and both of them are propagating westward with almost identical phase-speed during the time period of the integrations. No obvious change of the wave patterns is found at the levels in the model's troposphere. The amplitudes of both two waves at the uppermost level, however, exhibit rather significant oscillation with time, of which the periods are exactly 20 days and 25 days espectively.The explanation of this interesting phenomena is still under investigation.展开更多
Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance un...Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance unmanned aviation vehicle（UAV）. In order to improve efficiency it is proposed to construct a model management framework to perform the multi-objective optimization design of wing structure. The sufficient accurate approximation models of objective and constraint functions in the wing structure optimization model are built when using the model management framework, therefore in the evolutionary algorithm a number of finite element analyses can he avoided and the satisfactory multi-objective optimization results of the wing structure of the high altitude long endurance UAV are obtained.展开更多
Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems.As a process-oriented modelling approach,agent based model(ABM)plays an important role in reveali...Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems.As a process-oriented modelling approach,agent based model(ABM)plays an important role in revealing the driving forces of land change and understanding the process of land change.This paper starts from three aspects:The theory,application and modeling framework of ABM.First,we summarize the theoretical basis of ABM and introduce some related concepts.Then we expound the application and development of ABM in both urban land systems and agricultural land systems,and further introduce the case study of a model on Grain for Green Program in Hengduan Mountainous region,China.On the basis of combing the ABM modeling protocol,we propose the land system ABM modeling framework and process from the perspective of agents.In terms of urban land use,ABM research initially focused on the study of urban expansion based on landscape,then expanded to issues like urban residential separation,planning and zoning,ecological functions,etc.In terms of agricultural land use,ABM application presents more diverse and individualized features.Research topics include farmers’behavior,farmers’decision-making,planting systems,agricultural policy,etc.Compared to traditional models,ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data.However,due to its unique bottom-up model structure,ABM has an indispensable role in exploring the driving forces of land change and also the impact of human behavior on the environment.展开更多
Diesel molecular compositional model has important application for diesel quality prediction,blending,and molecular-level process model development.In this paper,different types of diesel molecular compositional and b...Diesel molecular compositional model has important application for diesel quality prediction,blending,and molecular-level process model development.In this paper,different types of diesel molecular compositional and blending models were constructed based on the SU-BEM framework.More than 1500 representative molecules were selected to form the molecular structure library.The probability density functions(PDFs)combination was determined by experimental data and experience.A quadratic optimization strategy combining genetic algorithm with local optimization algorithm was adopted to improve the accuracy of the compositional model.The model results show good agreement with the experimental data.The diesel blending model was constructed at the molecular-level based on the above diesel compositional models.The properties of the blending model accord with the experimental regulations.It is proved that the compositional models and blending model constructed have high accuracy and strong prediction capability,and are applicable to the industrial process.展开更多
After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtuali...After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application.展开更多
An approach for modeling a human cognitive framework in time-stressed decision making is presented. The recognitive and metacognitive processes that represent the cognitive framework are modeled by the colored Petri n...An approach for modeling a human cognitive framework in time-stressed decision making is presented. The recognitive and metacognitive processes that represent the cognitive framework are modeled by the colored Petri nets （CPNs）. A structural and behavioral analysis method is adopted to obtain the static and dynamic property used to verify the CPNs model of the cognitive framework. Finally, an example from the command and control radar recognition system is used to evaluate the feasibility and availability of the CPNs model adopted in practical systems.展开更多
The Zhongtiao Mountains, a typical exposure area of Precambrian rocks, are a concentration area of vari-ous types of copper deposit. The rocks were dated using several dating methods. Based on the age data ob-tained b...The Zhongtiao Mountains, a typical exposure area of Precambrian rocks, are a concentration area of vari-ous types of copper deposit. The rocks were dated using several dating methods. Based on the age data ob-tained by means of three methods, several aspects are dealt with: (1) the dating results obtained by differentmethods and their geological implications have been compared; (2) a chronotectonic framework has been con-structed by means of these reliable ages, which indicates that the ages of the rocks of the Proterozoic mobilebelt fall in a time span of 2400 to 2000 Ma during which global magmatic records are lacking and reflects theages of important events in the mobile belt; (3) according to the ages of inherited zircons, neodymium modelage of the depleted mantle sources (T_(DM)) and geochemical and geological data, a model of Precambrianchronocrustal structure has been constructed, representing a typical for the North China craton.展开更多
A framework is built, wherein hydrological/water quality model is used to measure watershed sustainability. For this framework, watershed sustainability has been defined and quantified by defining social, environmenta...A framework is built, wherein hydrological/water quality model is used to measure watershed sustainability. For this framework, watershed sustainability has been defined and quantified by defining social, environmental and biodiversity indicators. By providing weightage to these indicators, a “River Basin Sustainability Index” is built. The watershed sustainability is then calculated based on the concepts of reliability, resilience and vulnerability. The framework is then applied to a case study, where, based on watershed management principles, four land use scenarios are created in GIS. The Soil and Water Assessment Tool (SWAT) is used as a hydrology/water quality model. Based on the results the land uses are ranked for sustainability and policy implications have been discussed. This results show that landuse (both type and location) impact watershed sustainability. The existing land use is weak in environmental sustainability. Also, riparian zones play a critical role in watershed sustainability, although beyond certain width their contribution is not significant.展开更多
The current standard Unified Modeling Language(UML) could not model framework flexibility and extendibility adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A n...The current standard Unified Modeling Language(UML) could not model framework flexibility and extendibility adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A new UML profile that may customize UML for framework modeling was presented using the extension mechanisms of UML, providing a group of UML extensions to meet the needs of framework modeling. In this profile, the extended class diagrams and sequence diagrams were defined to straightforwardly identify the hot-spots and describe their instantiation restrictions. A transformation model based on design patterns was also put forward, such that the profile based framework design diagrams could be automatically mapped to the corresponding implementation diagrams. It was proved that the presented profile makes framework modeling more straightforwardly and therefore easier to understand and instantiate.展开更多
A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objective...A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured. The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.展开更多
With the intensi fed impact of human activities,most lakes have been severely disturbed and the lake ecosystem has been seriously damaged,which exerted a great impact on the living envi-ronment of human beings in the ...With the intensi fed impact of human activities,most lakes have been severely disturbed and the lake ecosystem has been seriously damaged,which exerted a great impact on the living envi-ronment of human beings in the lake basins.The health of the lake ecosystem has gradually become one of the hot issues in recent years.In this study,the water resources carrying capacity(WRCC)was used to reveal the chain rel ationship between human activities and water environ-ment in the economic dewelopment of the Dianchi Lake Basin in Kunming City of China during 2005-2015.Specifically,we chose 25 ewaluation indicators related to the water environment and socialeconomic activities,classified them into six subsystems,Le,the driwing force subsystem(D),the water resources si tuation and consumption subsystem(S),the water resources pressure subsystem(P),the water environmental situation subsystem(E),the response subsystem(R),and the management subsystem(M),and built a comprehensive assessment system-DSPERM frame-work model.Si mulated annealing-projection pursuit model which reflects the structure or feature of high-dimensional data was adopted to calculate the WRCC of the Dianchi Lake Basin during 2005-2015 by weighting each evaluation indicator and each subsystem of the DSPERM frame work model.The resuls show that the WRCC of the Dlanchi Lake Basin was in level II(medium carying capacity)from 2005 to 2012.Since 2013,the WRCC has been at level II(strong carying capacity),and from 2005 to 2015,it showed a gradual upward trend.The evaluation indicators of each subsystem varied greatly and exhibited different development trends.The indicators of the water resources pressure subsystem had the greatest impact on the WRCC,followed by the in-dicators of the water environmental si tuation subsystem and the water resources situation and consumption subsystem.We recommend that the DSPERM framework model and the simulated anneal ing-projection pursuit model constructed in this work can be used to analyze the dynamic changes of the WRCC over the years.They have the advantages of practicability and feasibilty,and can provide the basis for the scienti fic decision-making and comprehensive management of regional water environment planning.展开更多
Sustainability is a key objective of water resources management and this paper describes a modelling and decision support framework that achieves this, illustrated by applications on the UK Thames and Mekong river bas...Sustainability is a key objective of water resources management and this paper describes a modelling and decision support framework that achieves this, illustrated by applications on the UK Thames and Mekong river basins. The decision support framework contains several modules, including an interactive user＇s interface linked to a GIS, a geo-database, knowledge base, simulation models and optimization procedures. Based on the analysis of scenarios and proposed interventions, efficient modelling and optimization tools form a comprehensive integrated decision support framework for the analysis and operational management of water resources in the river basin, our emphasis has been on a practical implementation through careful screening of alternatives, consideration of the institutional framework and direct involvement of stakeholders in the decision making process. Operating in this environment is transparent, reproducible and auditable, securing the trust of all interested parties. This paper discusses its applications to water utilisation on the Mekong river basin and drought management of the Lower Thames stored reservoir system.展开更多
Different paradigms that relate verification and validation to the simulation model have different development process. A simulation model developing process based on Five-Object Framework (FOF) is discussed in this p...Different paradigms that relate verification and validation to the simulation model have different development process. A simulation model developing process based on Five-Object Framework (FOF) is discussed in this paper. An example is given to demonstrate the applications of the proposed method.展开更多
基金supported by the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT,Republic of Korea(Grant No.:RS-2024-00344752)supported by the Department of Integrative Biotechnology,Sungkyunkwan University(SKKU)and the BK21 FOUR Project,Republic of Korea.
文摘Peptide-based therapeutics hold great promise for the treatment of various diseases;however,their clinical application is often hindered by toxicity challenges.The accurate prediction of peptide toxicity is crucial for designing safe peptide-based therapeutics.While traditional experimental approaches are time-consuming and expensive,computational methods have emerged as viable alternatives,including similarity-based and machine learning(ML)-/deep learning(DL)-based methods.However,existing methods often struggle with robustness and generalizability.To address these challenges,we propose HyPepTox-Fuse,a novel framework that fuses protein language model(PLM)-based embeddings with conventional descriptors.HyPepTox-Fuse integrates ensemble PLM-based embeddings to achieve richer peptide representations by leveraging a cross-modal multi-head attention mechanism and Transformer architecture.A robust feature ranking and selection pipeline further refines conventional descriptors,thus enhancing prediction performance.Our framework outperforms state-of-the-art methods in cross-validation and independent evaluations,offering a scalable and reliable tool for peptide toxicity prediction.Moreover,we conducted a case study to validate the robustness and generalizability of HyPepTox-Fuse,highlighting its effectiveness in enhancing model performance.Furthermore,the HyPepTox-Fuse server is freely accessible at https://balalab-skku.org/HyPepTox-Fuse/and the source code is publicly available at https://github.com/cbbl-skku-org/HyPepTox-Fuse/.The study thus presents an intuitive platform for predicting peptide toxicity and supports reproducibility through openly available datasets.
基金supported by the National Natural Science Foundation of China(NSFC)under grant numbers of 52277222,52406256,and 52177217the Shanghai Science and Technology Development Fund under grant number 22ZR14445000the Artificial Intelligence for Research Paradigm Reform Enabling Discipline Leapfrog Program Project Funding Grant。
文摘The explosive growth of lithium-ion battery literature has led to severe knowledge overload,challenging researchers'ability to efficiently extract structured information.While large language models(LLMs)offer considerable potential for automating this task,their practical application in scientific domains is nonetheless constrained by high application programming interface(API)costs and computational resources required for fine-tuning.To address these limitations,a cognition-enhanced instruction framework(CEIF)is proposed,wherein a high-performance teacher model(such as DeepSeek-R1)provides dynamic feedback,prompt refinement,and training data optimization to guide the learning process of low-parameter models.Experimental results demonstrate that the low-parameter models(6B-9B)optimized via the CEIF achieve approximately 85%accuracy in battery literature extraction tasks,approaching the performance of GPT-4 while requiring only a single NVIDIA RTX 3090 GPU.Furthermore,the emergence of an"Aha moment"characterized by rapid performance improvement during specialized learning is observed,offering novel theoretical insights for the design and optimization of domainspecific models.
文摘Covalent organic frameworks(COFs)are crystalline materials composed of covalently bonded organic ligands with chemically permeable structures.Their crystallization is achieved by balancing thermal reversibility with the dynamic nature of the frameworks.Ionic covalent organic frameworks(ICOFs)are a subclass that incorporates ions in positive,negative,or zwitterionic forms into the frameworks.In particular,spiroborate-derived linkages enhance both the structural diversity and functionality of ICOFs.Unlike electroneutral COFs,ICOFs can be tailored by adjusting the types and arrangements of ions,influencing their formation mechanisms and physical properties.This study focuses on analyzing the graph-based structural characteristics of ICOFs with spiroborate linkages.We compute graph based entropy using hybrid topological descriptors that capture both local and global structural patterns.Furthermore,statistical regression models are developed to predict graph energies of larger-dimensional ICOF structures based on these descriptors.To ensure the robustness and accuracy of our results,we validated our findings using a pseudocode algorithm specifically designed for computing degree-based topological indices.This computational validation confirms the consistency of the derived descriptors and supports their applicability in quantitative structure-property relationship(QSPR)modeling.Overall,this approach provides valuable insights for future applications in material design and property prediction within the framework of ICOFs.
文摘Globally,the integration of traditional medicine and modern medicine has been recognized as a global health priority aimed at improving healthcare accessibility,cultural relevance,and therapeutic effectiveness.This review systematically examines the global landscape of traditional medicine-modern medicine integration by analyzing policy developments,regulatory frameworks,and clinical implementation models across various regions,including Asia,Africa,Europe,and the USA.The scope of the review encompasses five key domains:(1)global policy initiatives,(2)regulatory and institutional frameworks,(3)clinical integration models,(4)impacts and outcomes of integrative practices,and(5)challenges and barriers to implementation.Based on peer-reviewed literature and official health policy documents published between 2000 and 2025,the present review investigates how countries have operationalized clinical integration models combining traditional and complementary medicine.Although interest in traditional and complementary medicine has grown worldwide,persistent challenges,such as limited scientific validation,lack of standardization,and professional resistance,continue to hinder progress.This review concludes that successful and sustainable integration requires evidence-based clinical approaches,inclusive regulatory reforms,and coordinated policy strategies.Countries such as China,India,and Brazil have made significant advances,offering valuable models for future implementation worldwide.
基金funded by the Chongqing Water Resources Bureau,China(Project No.CQS24C00836).
文摘We proposes an AI-assisted framework for integrated natural disaster prevention and emergency response,leveraging the DeepSeek large language model(LLM)to advance intelligent decision-making in geohazard management.We systematically analyze the technical pathways for deploying LLMs in disaster scenarios,emphasizing three breakthrough directions:(1)knowledge graph-driven dynamic risk modeling,(2)reinforcement learning-optimized emergency decision systems,and(3)secure local deployment architectures.The DeepSeek model demonstrates unique advantages through its hybrid reasoning mechanism combining semantic analysis with geospatial pattern recognition,enabling cost-effective processing of multi-source data spanning historical disaster records,real-time IoT sensor feeds,and socio-environmental parameters.A modular system architecture is designed to achieve three critical objectives:(a)automated construction of domain-specific knowledge graphs through unsupervised learning of disaster physics relationships,(b)scenario-adaptive resource allocation using risk simulations,and(c)preserving emergency coordination via federated learning across distributed response nodes.The proposed local deployment paradigm addresses critical data security concerns in cross-border disaster management while complying with the FAIR principles(Findable,Accessible,Interoperable,Reusable)for geoscientific data governance.This work establishes a methodological foundation for next-generation AI-earth science convergence in disaster mitigation.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
基金supported by the Major State Basic Research Development Program(No.2012CB 214803)the China's National Science & Technology Special Project (No.2011ZX05004-005-03)+1 种基金the PetroChina Youth Innovation Foundation(No.2011D-5006-0105)the Key Subject Construction Project of Sichuan Province,China(No.SZD0414)
文摘The Upper Triassic Xujiahe （须家河） Formation in the Sichuan （四川） Basin, Southwest China is distinctive for the basin-scale sand deposition. This relatively rare sedimentary phenomenon has not been well interpreted. Here we addressed this issue by discussing sedimentary framework and conceptual model. Analysis of sedimentary setting implied that the basin received transgression during the deposition. It had multiple provenance supplies and river networks, as being surrounded by old- lands in multiple directions including the north, east and south. Thus, the basin was generally charac-terized by coastal and widely open and shallow lacustrine deposition during the Late Triassic Xujiahe period. This is similar to the modern well-known Poyang （鄱阳） Lake. Therefore, we investigated the framework and conceptual model of the Sichuan Basin during the Xujiahe period with an analogue to the Poyang Lake. Results show that the conceptual model of the deposition can be divided into transgressive and regressive stages. The first, third and fifth mem- bers of the formation are in transgressive stage and the deposits are dominated by shore and shallow lacustrine mud. In contrast, the deposition is mainly of braided river channel sand deposits during the regressive stage, mainly including the second, fourth and sixth members of the formation. The sand deposited in almost the entire basin because of the lateral migration and forward moving of the cross networks of the braided rivers. The multiple alternations of short and rapid transgression and relatively long regression are beneficial to the basin-scale sand deposition. Thus, the main channel of the braided river and its extensional areas are favorable for the development of hydrocarbon reservoir. This provides practical significance to the reservoir evaluation and exploration. In addition, the results also justify the relatively distinctive sedimentary phenomenon in the study area and may also have im- plications for understanding the large-scale sand deposition elsewhere.
文摘The dynamical framework of the nine-level version of the IAP AGCM is presented in this paper. The emphasis of the model's description is put on the following two aspects:(1) A model's standard atmosphere, which is a satisfactory approximation to the observed troposphere and lower stratosphere standard atmosphere, is introduced into the equations of the model to permit a more accurate calculation of the vertical transport terms, especially near the tropopause; (2) The vertical levels of the model are carefully selected to guarantee a smooth dependence of layer thickness upon pressure in order to reduce the truncation error involved in the unequal interval vertical finite-differencing. For testing the model, two kinds of linear baroclinic Rossby-Haurwitz waves, one of which has a dynamically stable vertical structure and the other has a relatively unstable one, are constructed to provide initial conditions for numerical experiments. The two waves have been integrated for more than 300 days and 100 days respectively by using the model and both of them are propagating westward with almost identical phase-speed during the time period of the integrations. No obvious change of the wave patterns is found at the levels in the model's troposphere. The amplitudes of both two waves at the uppermost level, however, exhibit rather significant oscillation with time, of which the periods are exactly 20 days and 25 days espectively.The explanation of this interesting phenomena is still under investigation.
文摘Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance unmanned aviation vehicle（UAV）. In order to improve efficiency it is proposed to construct a model management framework to perform the multi-objective optimization design of wing structure. The sufficient accurate approximation models of objective and constraint functions in the wing structure optimization model are built when using the model management framework, therefore in the evolutionary algorithm a number of finite element analyses can he avoided and the satisfactory multi-objective optimization results of the wing structure of the high altitude long endurance UAV are obtained.
基金National Natural Science Foundation of China,No.41571098,No.41530749National Key R&D Program of China,No.2017YFC1502903,No.2018YFC1508805。
文摘Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems.As a process-oriented modelling approach,agent based model(ABM)plays an important role in revealing the driving forces of land change and understanding the process of land change.This paper starts from three aspects:The theory,application and modeling framework of ABM.First,we summarize the theoretical basis of ABM and introduce some related concepts.Then we expound the application and development of ABM in both urban land systems and agricultural land systems,and further introduce the case study of a model on Grain for Green Program in Hengduan Mountainous region,China.On the basis of combing the ABM modeling protocol,we propose the land system ABM modeling framework and process from the perspective of agents.In terms of urban land use,ABM research initially focused on the study of urban expansion based on landscape,then expanded to issues like urban residential separation,planning and zoning,ecological functions,etc.In terms of agricultural land use,ABM application presents more diverse and individualized features.Research topics include farmers’behavior,farmers’decision-making,planting systems,agricultural policy,etc.Compared to traditional models,ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data.However,due to its unique bottom-up model structure,ABM has an indispensable role in exploring the driving forces of land change and also the impact of human behavior on the environment.
基金supported by the SINOPEC R&D Program(grant number 119014-1)
文摘Diesel molecular compositional model has important application for diesel quality prediction,blending,and molecular-level process model development.In this paper,different types of diesel molecular compositional and blending models were constructed based on the SU-BEM framework.More than 1500 representative molecules were selected to form the molecular structure library.The probability density functions(PDFs)combination was determined by experimental data and experience.A quadratic optimization strategy combining genetic algorithm with local optimization algorithm was adopted to improve the accuracy of the compositional model.The model results show good agreement with the experimental data.The diesel blending model was constructed at the molecular-level based on the above diesel compositional models.The properties of the blending model accord with the experimental regulations.It is proved that the compositional models and blending model constructed have high accuracy and strong prediction capability,and are applicable to the industrial process.
文摘After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application.
基金supported by the National Natural Science Foundation of China(60874068).
文摘An approach for modeling a human cognitive framework in time-stressed decision making is presented. The recognitive and metacognitive processes that represent the cognitive framework are modeled by the colored Petri nets （CPNs）. A structural and behavioral analysis method is adopted to obtain the static and dynamic property used to verify the CPNs model of the cognitive framework. Finally, an example from the command and control radar recognition system is used to evaluate the feasibility and availability of the CPNs model adopted in practical systems.
文摘The Zhongtiao Mountains, a typical exposure area of Precambrian rocks, are a concentration area of vari-ous types of copper deposit. The rocks were dated using several dating methods. Based on the age data ob-tained by means of three methods, several aspects are dealt with: (1) the dating results obtained by differentmethods and their geological implications have been compared; (2) a chronotectonic framework has been con-structed by means of these reliable ages, which indicates that the ages of the rocks of the Proterozoic mobilebelt fall in a time span of 2400 to 2000 Ma during which global magmatic records are lacking and reflects theages of important events in the mobile belt; (3) according to the ages of inherited zircons, neodymium modelage of the depleted mantle sources (T_(DM)) and geochemical and geological data, a model of Precambrianchronocrustal structure has been constructed, representing a typical for the North China craton.
文摘A framework is built, wherein hydrological/water quality model is used to measure watershed sustainability. For this framework, watershed sustainability has been defined and quantified by defining social, environmental and biodiversity indicators. By providing weightage to these indicators, a “River Basin Sustainability Index” is built. The watershed sustainability is then calculated based on the concepts of reliability, resilience and vulnerability. The framework is then applied to a case study, where, based on watershed management principles, four land use scenarios are created in GIS. The Soil and Water Assessment Tool (SWAT) is used as a hydrology/water quality model. Based on the results the land uses are ranked for sustainability and policy implications have been discussed. This results show that landuse (both type and location) impact watershed sustainability. The existing land use is weak in environmental sustainability. Also, riparian zones play a critical role in watershed sustainability, although beyond certain width their contribution is not significant.
文摘The current standard Unified Modeling Language(UML) could not model framework flexibility and extendibility adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A new UML profile that may customize UML for framework modeling was presented using the extension mechanisms of UML, providing a group of UML extensions to meet the needs of framework modeling. In this profile, the extended class diagrams and sequence diagrams were defined to straightforwardly identify the hot-spots and describe their instantiation restrictions. A transformation model based on design patterns was also put forward, such that the profile based framework design diagrams could be automatically mapped to the corresponding implementation diagrams. It was proved that the presented profile makes framework modeling more straightforwardly and therefore easier to understand and instantiate.
文摘A GIS audit framework is necessary considering the diverse nature of GIS with regard to components, applications and industry. In practice, checklists are generated during the audit process based on specific objectives. There is no standardized list of items that can be used as a reference. The purpose of this study was to develop a GIS audit framework as a foundation for GIS audits. The framework provides that comprehensive approach to various GIS aspects during the audit process. The design builds on a developed conceptual framework where most significant categories of GIS audit parameters namely data quality, software utilization, GIS competency and procedures (work flows) were identified. The study adopted a reductive model approach to simplify the complexity associated with each category of GIS audit parameter. The resultant audit elements for each category are organized in a matrix that forms an integral part of the framework. The columns comprise audit goal, audit questions and audit subjects as indicators which are qualitatively measured. The rows comprise the parameters (data quality, software utilization, personnel competency and procedure (workflows)). To use the framework, an auditor only needs to create an audit checklist that consists of particular parameters and indicators from the framework depending on audit objective. As part of an on-going research, the next step will involve validating the framework through a mock testing process.
基金This research was supported by the National Social Sciance Foundation of China(20&ZD091)the Sciance and Technology Department Project of Sichuan Province,China(21 RICX0358,2019JDJQ0006)the Social Science Planning Project of Sichuan Province,China(SC18B027).
文摘With the intensi fed impact of human activities,most lakes have been severely disturbed and the lake ecosystem has been seriously damaged,which exerted a great impact on the living envi-ronment of human beings in the lake basins.The health of the lake ecosystem has gradually become one of the hot issues in recent years.In this study,the water resources carrying capacity(WRCC)was used to reveal the chain rel ationship between human activities and water environ-ment in the economic dewelopment of the Dianchi Lake Basin in Kunming City of China during 2005-2015.Specifically,we chose 25 ewaluation indicators related to the water environment and socialeconomic activities,classified them into six subsystems,Le,the driwing force subsystem(D),the water resources si tuation and consumption subsystem(S),the water resources pressure subsystem(P),the water environmental situation subsystem(E),the response subsystem(R),and the management subsystem(M),and built a comprehensive assessment system-DSPERM frame-work model.Si mulated annealing-projection pursuit model which reflects the structure or feature of high-dimensional data was adopted to calculate the WRCC of the Dianchi Lake Basin during 2005-2015 by weighting each evaluation indicator and each subsystem of the DSPERM frame work model.The resuls show that the WRCC of the Dlanchi Lake Basin was in level II(medium carying capacity)from 2005 to 2012.Since 2013,the WRCC has been at level II(strong carying capacity),and from 2005 to 2015,it showed a gradual upward trend.The evaluation indicators of each subsystem varied greatly and exhibited different development trends.The indicators of the water resources pressure subsystem had the greatest impact on the WRCC,followed by the in-dicators of the water environmental si tuation subsystem and the water resources situation and consumption subsystem.We recommend that the DSPERM framework model and the simulated anneal ing-projection pursuit model constructed in this work can be used to analyze the dynamic changes of the WRCC over the years.They have the advantages of practicability and feasibilty,and can provide the basis for the scienti fic decision-making and comprehensive management of regional water environment planning.
文摘Sustainability is a key objective of water resources management and this paper describes a modelling and decision support framework that achieves this, illustrated by applications on the UK Thames and Mekong river basins. The decision support framework contains several modules, including an interactive user＇s interface linked to a GIS, a geo-database, knowledge base, simulation models and optimization procedures. Based on the analysis of scenarios and proposed interventions, efficient modelling and optimization tools form a comprehensive integrated decision support framework for the analysis and operational management of water resources in the river basin, our emphasis has been on a practical implementation through careful screening of alternatives, consideration of the institutional framework and direct involvement of stakeholders in the decision making process. Operating in this environment is transparent, reproducible and auditable, securing the trust of all interested parties. This paper discusses its applications to water utilisation on the Mekong river basin and drought management of the Lower Thames stored reservoir system.
文摘Different paradigms that relate verification and validation to the simulation model have different development process. A simulation model developing process based on Five-Object Framework (FOF) is discussed in this paper. An example is given to demonstrate the applications of the proposed method.
